This paper proposes FlashLinQ-a synchronous peer-to-peer wireless PHY/MAC network architecture. FlashLinQ leverages the fine-grained parallel channel access offered by OFDM and incorporates an analog energy-level-based signaling scheme that enables signal-to-interference ratio (SIR)-based distributed scheduling. This new signaling mechanism, and the concomitant scheduling algorithm, enables efficient channel-aware spatial resource allocation, leading to significant gains over a CSMA/CA system using RTS/CTS. FlashLinQ is a complete system architecture including: 1) timing and frequency synchronization derived from cellular spectrum; 2) peer discovery; 3) link management; and 4) channel-aware distributed power, data rate, and link scheduling. FlashLinQ has been implemented for operation over licensed spectrum on a digital signal processor/field-programmable gate array (DSP/FPGA) platform. In this paper, we present FlashLinQ performance results derived from both measurements and simulations.

We study two building-block models of interference-limited wireless networks, motivated by the problem of joint Peer-to-Peer and Wide Area Network design. In the first case, a single “long-range” transmitter interferes with multiple parallel “short-range” transmissions, and, in the second case, multiple short-range transmitters interfere with a single long-range receiver. We identify the maximal degree-of-freedom region of the former network and show that multilevel superposition coding by the long-range transmitter performs optimally. Moreover, a simple power control strategy, performed by the long-range transmitter, achieves a region that is within one bit of the capacity region, under certain channel conditions. For the latter network, we show that short-range transmitter power control is degree-of-freedom optimal under certain channel conditions.

In this paper, we consider a communication scenario in which the primary and the cognitive radios wish to communicate to different receivers, subject to mutual interference. In the model that we use, the cognitive radio has noncausal knowledge of the primary radio's codeword. We characterize the largest rate at which the cognitive radio can reliably communicate under the constraint that 1)no rate degradationis created for the primary user, and 2) the primary receiver uses asingle-user decoderjust as it would in the absence of the cognitive radio. The result holds in a “low-interference” regime in which the cognitive radio is closer to its receiver than to the primary receiver. In this regime, our results are subsumed by the results derived in a concurrent and independent work (Wu, 2007). We also demonstrate that, in a “high-interference” regime, multiuser decoding at the primary receiver is optimal from the standpoint of maximal jointly achievable rates for the primary and cognitive users.

Cognitive radios have been proposed as a means to implement efficient reuse of the licensed spectrum. The key feature of a cognitive radio is its ability to recognize the primary (licensed) user and adapt its communication strategy to minimize the interference that it generates. We consider a communication scenario in which the primary and the cognitive user wish to communicate to different receivers, subject to mutual interference. Modeling the cognitive radio as a transmitter with side-information about the primary transmission, we characterize the largest rate at which the cognitive radio can reliably communicate under the constraint that (i) no interference is created for the primary user, and (ii) the primary encoder-decoder pair is oblivious to the presence of the cognitive radio.

In this correspondence, we study the capacity region of a general wireless network by deriving fundamental upper bounds on a class of linear functionals of the rate tuples at which joint reliable communication can take place. The widely studied transport capacity is a specific linear functional: the coefficient of the rate between a pair of nodes is equal to the Euclidean distance between them. The upper bound on the linear functionals of the capacity region is used to derive upper bounds to scaling laws for generalized transport capacity: the coefficient of the rate between a pair of nodes is equal to some arbitrary function of the Euclidean distance between them, for a class of minimum distance networks. This upper bound to the scaling law meets that achievable by multihop communication over these networks for a wide class of channel conditions; this shows the optimality, in the scaling-law sense, of multihop communication when studying generalized transport capacity of wireless networks.

We derive upper bounds on the transport capacity of wireless networks. The bounds obtained are solely dependent on the geographic locations and power constraints of the nodes. As a result of this derivation, we are able to conclude the optimality, in the sense of scaling of transport capacity with the number of nodes, of a multihop communication strategy for a class of network topologies.